Simon Zhang

Ph.D. Candidate
Department of Computer Science
Purdue University
Email: zhan4125 AT purdue dot edu

GitHub

I am working on my Ph.D. of Computer Science at Purdue University.

I was a former Ph.D. student at the Ohio State University where I received my M.S. from the Department of Computer Science and Engineering.

I received my B.S. in Computer Science from Cornell University.

My research focus is in the areas of graph learning and algorithms, topological data analysis, and high performance computing. My advisor is Professor Tamal Dey

I have worked at Argonne National Laboratory in the Data Science and Learning Division in the summers of 2021 and 2022.

Publications

Simon Zhang, Cheng Xin, Tamal K. Dey "Expressive Higher-Order Link Prediction through Hypergraph Symmetry Breaking " Under Review

Simon Zhang, Ryan DeMilt, Kun Jin, Cathy Xia "Adversarial Data Augmentations for Out-of-Distribution Generalization " in the Second Workshop on Spurious Correlations, Invariance and Stability (ICML 2023)

Simon Zhang, Soham Mukherjee, Tamal K. Dey "GEFL: Extended Filtration Learning for Graph Classification" in the Proceedings of the 1st Learning on Graphs Conference 2022

GEFL is released as open source on GitHub.

Tamal K. Dey, Simon Zhang "Approximating 1-Wasserstein Distance between Persistence Diagrams by Graph Sparsification" in 2022 Proceedings of SIAM Symposium on Algorithm Engineering and Experiments .

PDoptFlow is released as open source on GitHub.

Simon Zhang, Mengbai Xiao, Hao Wang. "GPU-Accelerated Computation of Vietoris-Rips Persistence Barcodes" in Proceedings of the 36th Symposium on Computational Geometry.

Ripser++ is released as open source on GitHub.

SoCG 20 minute presentation slides

Simon Zhang, Mengbai Xiao, Chengxin Guo, Liang Geng, Hao Wang, et al. "HYPHA: a Framework based on Separation of Parallelisms to Accelerate Persistent Homology Matrix Reduction", in Proceedings of the 33rd ACM International Conference on Supercomputing.

HYPHA is released as open source on GitHub.

Yin Huai, Rubao Lee, Simon Zhang, Cathy H. Xia, et al. "DOT: a Matrix Model for Analyzing, Optimizing and Deploying Software for Big Data Analytics in Distributed Systems", Proceedings of the 2nd ACM Symposium on Cloud Computing.